Automated quality assurance routines for fMRI data applied to a multicenter study

  • Stöcker T
  • Schneider F
  • Klein M
 et al. 
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Abstract

Standard procedures to achieve quality assessment (QA) of functional
magnetic resonance imaging (fMRI) data are of great importance. A
standardized and fully automated procedure for QA is presented that
allows for classification of data quality and the detection of artifacts
by inspecting temporal variations. The application of the procedure
on phantom measurements was used to check scanner and stimulation
hardware performance. In vivo imaging data were checked efficiently
for artifacts within the standard fMRI post-processing procedure
by realignment. Standardized and routinely carried out QA is essential
for extensive data amounts as collected in fMRI, especially in multicenter
studies. Furthermore, for the comparison of two different groups,
it is important to ensure that data quality is approximately equal
to avoid possible misinterpretations. This is shown by example, and
criteria to quantify differences of data quality between two groups
are defined. Hum Brain Mapp 25:237–246, 2005. {\copyright} 2005 Wiley-Liss,
Inc.

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Authors

  • Tony Stöcker

  • Frank Schneider

  • Martina Klein

  • Ute Habel

  • Thilo Kellermann

  • Karl Zilles

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